Systems and methods for sentence comparison and sentence-based search

A non-transitory processor-readable storage medium having stored thereon processor-executable software instructions configured to cause a processor to perform operations for creating a searchable database using matrix-theoretic functions of graph-theoretic representations of sentences, the operations comprising:

• receiving unstructured training text;
• performing a natural language processor (NLP) pipeline on the unstructured training text, the unstructured training text comprising sentences;
• creating sentence matrix representations of the unstructured training text based on output of performing the NLP pipeline on the unstructured training text, each of the sentence matrix representations corresponding to a semantic structure of an individual sentence;
• storing the sentence matrix representations in an indexed datastore;
• combining the sentence matrix representations as a sum to form a training matrix;
• performing a Singular Value Decomposition (SVD) computation on the training matrix to calculate SVD components;
• storing the calculated SVD components in the indexed datastore;
• applying the calculated SVD components to each of the sentence matrix representations to form a low-dimensional matrix representation for each of the sentences of the unstructured training text;
• and
• storing the low-dimensional matrix representations in the indexed datastore.

A computing device for creating a searchable database using semantic dependencies, comprising:

• means for receiving unstructured training text;
• means for performing a natural language processor (NLP) pipeline on the unstructured training text, the unstructured training text comprising sentences;
• means for creating sentence matrix representations of the unstructured training text based on output of performing the NLP pipeline on the unstructured training text, each of the sentence matrix representations corresponding to a semantic structure of an individual sentence;
• means for storing the sentence matrix representations in an indexed datastore;
• means for combining the sentence matrix representations as a sum to form a training matrix;
• means for performing a Singular Value Decomposition (SVD) computation on the training matrix to calculate SVD components;
• means for storing the calculated SVD components in the indexed datastore;
• means for applying the calculated SVD components to each of the sentence matrix representations to form a low-dimensional matrix representation for each of the sentences of the unstructured training text;
• and
• storing the low-dimensional matrix representations in the indexed datastore.

A method for creating a searchable database using semantic dependencies comprising:

• receiving unstructured training text;
• performing a natural language processor (NLP) pipeline on the unstructured training text, the unstructured training text comprising sentences;
• creating sentence matrix representations of the unstructured training text based on output of performing the NLP pipeline on the unstructured training text, each of the sentence matrix representations corresponding to a semantic structure of an individual sentence;
• storing the sentence matrix representations in an indexed datastore;
• combining the stored sentence matrix representations as a sum to form a training matrix;
• performing a Singular Value Decomposition (SVD) computation on the training matrix to calculate SVD components;
• storing the calculated SVD components in the indexed datastore;
• applying the calculated SVD components to each of the sentence matrix representations to form a low-dimensional matrix representation for each of the sentences of the unstructured training text;
• and
• storing the low-dimensional matrix representations in the indexed datastore.